Dipesh Oli, Buddhi Gyawali, Shikha Acharya, Samuel Oshikoya
{"title":"Factors influencing learning attitude of farmers regarding adoption of farming technologies in farms of Kentucky, USA","authors":"Dipesh Oli, Buddhi Gyawali, Shikha Acharya, Samuel Oshikoya","doi":"10.1016/j.atech.2025.100801","DOIUrl":null,"url":null,"abstract":"<div><div>Understanding farmers’ learning attitudes towards agricultural technologies and the factors affecting their adoption behavior is crucial in today's era of rapid technological advancement. This study focuses on assessing various socioeconomic factors influencing farmers’ learning behavior regarding technologies in farming operations and understanding farmers’ views on the future of precision agriculture in crop and livestock production. The study also examined the preferred methods farmers use for learning. Using R-studio, the binary logistic regression model was employed to analyze the survey data. The results suggest that the education level and social media use significantly affected farmers’ learning attitudes. In contrast factors such as gender, age, income level, related expertise, and farming experience had no significant impact. The study also concluded that seminars, workshops, and training are preferred learning methods. Thus, it is recommended that federal and state agencies and universities' extension systems should focus on combining these preferred learning methods with various social media platforms to disseminate the necessary information, knowledge, and skills to farmers, supporting better adoption of agricultural technologies.</div></div>","PeriodicalId":74813,"journal":{"name":"Smart agricultural technology","volume":"10 ","pages":"Article 100801"},"PeriodicalIF":6.3000,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart agricultural technology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772375525000358","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
Understanding farmers’ learning attitudes towards agricultural technologies and the factors affecting their adoption behavior is crucial in today's era of rapid technological advancement. This study focuses on assessing various socioeconomic factors influencing farmers’ learning behavior regarding technologies in farming operations and understanding farmers’ views on the future of precision agriculture in crop and livestock production. The study also examined the preferred methods farmers use for learning. Using R-studio, the binary logistic regression model was employed to analyze the survey data. The results suggest that the education level and social media use significantly affected farmers’ learning attitudes. In contrast factors such as gender, age, income level, related expertise, and farming experience had no significant impact. The study also concluded that seminars, workshops, and training are preferred learning methods. Thus, it is recommended that federal and state agencies and universities' extension systems should focus on combining these preferred learning methods with various social media platforms to disseminate the necessary information, knowledge, and skills to farmers, supporting better adoption of agricultural technologies.